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AWS Batch

87
247
+ 1
6
Google Cloud Run

274
228
+ 1
62
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AWS Batch vs Google Cloud Run: What are the differences?

Developers describe AWS Batch as "Fully Managed Batch Processing at Any Scale". It enables developers, scientists, and engineers to easily and efficiently run hundreds of thousands of batch computing jobs on AWS. It dynamically provisions the optimal quantity and type of compute resources (e.g., CPU or memory optimized instances) based on the volume and specific resource requirements of the batch jobs submitted. On the other hand, Google Cloud Run is detailed as "Run stateless HTTP containers on a fully managed environment or in your own GKE cluster". A managed compute platform that enables you to run stateless containers that are invocable via HTTP requests. It's serverless by abstracting away all infrastructure management.

AWS Batch and Google Cloud Run can be categorized as "Serverless / Task Processing" tools.

Decisions about AWS Batch and Google Cloud Run
Clifford Crerar
Software Engineer at Bidvest Advisory Services · | 9 upvotes · 66.4K views

Run cloud service containers instead of cloud-native services

  • Running containers means that your microservices are not "cooked" into a cloud provider's architecture.
  • Moving from one cloud to the next means that you simply spin up new instances of your containers in the new cloud using that cloud's container service.
  • Start redirecting your traffic to the new resources.
  • Turn off the containers in the cloud you migrated from.
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Pros of AWS Batch
Pros of Google Cloud Run
  • 3
    Containerized
  • 3
    Scalable
  • 11
    HTTPS endpoints
  • 10
    Fully managed
  • 10
    Pay per use
  • 7
    Concurrency: multiple requests sent to each container
  • 7
    Deploy containers
  • 7
    Serverless
  • 6
    Custom domains with auto SSL
  • 4
    "Invoke IAM permission" to manage authentication
  • 0
    Cons

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Cons of AWS Batch
Cons of Google Cloud Run
  • 3
    More overhead than lambda
  • 1
    Image management
    Be the first to leave a con

    Sign up to add or upvote consMake informed product decisions

    What is AWS Batch?

    It enables developers, scientists, and engineers to easily and efficiently run hundreds of thousands of batch computing jobs on AWS. It dynamically provisions the optimal quantity and type of compute resources (e.g., CPU or memory optimized instances) based on the volume and specific resource requirements of the batch jobs submitted.

    What is Google Cloud Run?

    A managed compute platform that enables you to run stateless containers that are invocable via HTTP requests. It's serverless by abstracting away all infrastructure management.

    Need advice about which tool to choose?Ask the StackShare community!

    What companies use AWS Batch?
    What companies use Google Cloud Run?
    See which teams inside your own company are using AWS Batch or Google Cloud Run.
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    What tools integrate with AWS Batch?
    What tools integrate with Google Cloud Run?

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    What are some alternatives to AWS Batch and Google Cloud Run?
    AWS Lambda
    AWS Lambda is a compute service that runs your code in response to events and automatically manages the underlying compute resources for you. You can use AWS Lambda to extend other AWS services with custom logic, or create your own back-end services that operate at AWS scale, performance, and security.
    Beanstalk
    A single process to commit code, review with the team, and deploy the final result to your customers.
    Airflow
    Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command lines utilities makes performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress and troubleshoot issues when needed.
    Kubernetes
    Kubernetes is an open source orchestration system for Docker containers. It handles scheduling onto nodes in a compute cluster and actively manages workloads to ensure that their state matches the users declared intentions.
    Serverless
    Build applications comprised of microservices that run in response to events, auto-scale for you, and only charge you when they run. This lowers the total cost of maintaining your apps, enabling you to build more logic, faster. The Framework uses new event-driven compute services, like AWS Lambda, Google CloudFunctions, and more.
    See all alternatives